code: def format_score(forecast_df, col_name="pred", label_shift=5):
      pred = process_predicted(forecast_df, col_name=col_name)
      pred = get_shifted_label(
          pred, shifts=-label_shift, col_shift=col_name
      )
      pred = pred.dropna()[col_name]
      return pred
  
imports: from pathlib import Path
  from typing import Union
  import numpy
  import pandas
  import tensorflow.compat.v1
  import data_formatters.base
  import expt_settings.configs
  import libs.hyperparam_opt
  import libs.tft_model
  import libs.utils
  import os
  import datetime
  from qlib.model.base import ModelFT
  from qlib.data.dataset import DatasetH
  from qlib.data.dataset.handler import DataHandlerLP
label_desc: Use image node_id 5 for calling a global function with example usage: format_score(forecast_df, col_name, label_shift) and returns: pred